Combining Control by CTA and Dynamic En Route Speed ...

Combining Control by CTA and

Dynamic En Route Speed

Adjustment to Improve Ground

Delay Program Performance

James C. Jones, University of Maryland

David J. Lovell, University of Maryland

Michael O. Ball, University of Maryland

1

11th FAA/EUROCONTROL ATM R&D Seminar

Lisbon, Portugal

June 23-26, 2015

Overview

• Motivation and Background

• Proposed changes to GDP planning

architecture

• New GDP planning integer programming

models

• Results

• Summary

2

Motivating Ideas

• Control by CTA

– Klooster et al [2009], McDonald and Bronsvoort [2012], Nieuwenhuisen,

and Gelder [2012], Delta (Atilla), United Airlines (Heathrow)

• Speed Control

– GDP planning: Delgado and Prats [2011], [2013], [2014], Prats and

Hansen [2011], Jones [2014]

– Tactical planning: Neuman and Erzberger [1991], Knorr et al [2011],

Swenson et al [2011], Jones et al [2013], ATD-1, Extended Metering

• Collaborative Decision Making

– Wambsganns [1993], Ball et al [2001], Vossen and Ball [2006], [2006],

Fearing et al [2011]

• Hedging Under Uncertainty

– Capacity Uncertainty: Richetta and Odoni, [1993], Ball et al [2003],

Mukherjee and Hansen [2007], Ball et al [2010]

– Demand Uncertainty: Ball et al [2001]

3

GDP Background

• When faced with inclement weather the capacity

of airports is often insufficient to meet demand

• To deal with these imbalances FAA managers

impose a Ground Delay Program (GDP)

• Since inclement weather will often clear prior to

the end of the GDP an exemption radius is set

– Removes delays to long haul flights

– Can reduce overall delay if the weather clears earlier

than expected

4

Speed Control in Ground Delay Programs

• During GDPs, flight managers assign a controlled time of

departure (CTD) to flights

• Assigning Controlled Times of Arrival (CTAs) in lieu of

CTDs may offer a more attractive means of transferring

delay

– Provides carriers more flexibility and control

– Allows for system-wide trade-offs

5STD CTD CTASTA

GDTravel Time

Delay allocation under conventional GDP Planning






delay



6STD CTDmax

CTASTA

GDmin

Travel Time

Delay allocation under CTA based GDP Planning

CTDmin

Variable

Delay






delay



7STD CTDmax

CTASTA

GDmin

Travel Time

Delay allocation under CTA based GDP Planning

CTDmin

Variable

DelayFAA

Airlines






delay



8

GDP Planning Process

Current Practice: RBS with Exemptions

• Flights are assigned to available slots based

on the order they appear in the schedule

• Exempt flights receive priority

9

Shortcomings of Exemptions

• DAL490 and UA12 cannot make substitutions

since exempt flights are airborne

• Can add additional delay to flights or cause

additional cancellations10

Cancellation and Substitution process in current CDM framework.

Advantage of Adding Speed Control

• With speed control Delta and United can

reassign airborne flights and achieve better

metrics

11

Cancellation and Substitution process without exemptions. Delta and

United can substitute and improve their on-time performance.

Fuel Usage Characteristics

• Fuel efficiency is a concave

function of speed

• General Characteristics:– Cost curves are relatively flat

– Cruise speeds can often exceed the

maximum range

– Slowing down during cruise can

increase specific range

• Airlines could adjust speeds

of flights to reduce ground

delays during GDPs at a

relatively small fuel penalty

Maximum

Range

Specific

Range

NM/ton

Mach

Number

Range of

Operation

vmin vmax

12

New GDP Architecture

• FAA procedural modifications– Replace the use of CTDs with CTAs in GDP planning

– Remove the exemption radius

– Allow en route speed changes by carriers

• Airline decision making modifications– Incorporate speed changes into substitution and

cancellation process

– Introduce a new stochastic optimization model to

support airline decision-making with substitutions and

cancellations

• Model matches flights to assigned capacity

• Allows airlines to hedge for early weather clearance13

AA

Conventional GDP Planning

14

Airborne Flights:

Flight Positions and

ETAs, AC speeds

Flight on Ground:

Flight Schedule

Assign

CTDs to

Airlines

DB-

RBS

FCFS

Substitute

and Cancel

Flights

Compression

FAA FAAAirlines

Data

Algorithms

Allocations

Airline Decisions

AA


15

Assign

CTDs to

Airlines

DB-

RBS

FCFS

Substitute

and Cancel

Flights

Compression

Departure

Time

Changes

Flight

Cancellations

FAA FAAAirlines

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

Mechanisms

AA


16

Assign

CTDs to

Airlines

DB-

RBS

FCFS

Substitute

and Cancel

Flights

Compression

Departure

Time

Changes

Data

Algorithms

Allocations

Airline Decisions

Mechanisms

FAA FAAAirlines

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

AA


17

Assign

CTDs to

Airlines

DB-

RBS

FCFS

Substitute

and Cancel

Flights

Compression

FAA FAAAirlines

• System has limited measures for recourse in the

presence of unplanned conditions

• Slow to react in the presence of early clearance of

weather

• Cannot take full advantage of opportunities for

potential trades

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

AA

CTA Based GDP Planning

18

Assign

CTAs to

Airlines

RBS

FCFS

Substitute

and Cancel

Flights+ + Compression

FAA FAAAirlines

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

AA


19

Assign

CTAs to

Airlines

RBS

FCFS

Substitute

and Cancel


FAA FAAAirlines

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

AA


20

Assign

CTAs to

Airlines

RBS

FCFS

Substitute

and Cancel


Departure

Time

Changes

HedgingFlight

Cancellations

Speed

Control

FAA FAAAirlines

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

Mechanisms

AA


21

Assign

CTAs to

Airlines

RBS

FCFS

Substitute

and Cancel


Departure

Time

Changes

Speed

Control

FAA FAAAirlines

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

Mechanisms

AA


22

Assign

CTAs to

Airlines

RBS

FCFS

Substitute

and Cancel


FAA FAAAirlines

• System is more flexible in accommodating

unplanned conditions

• More effective delay in the presence of early

clearance of weather

• Allows additional substitution opportunities

• Adjustments can be performed to react to both major

and minor perturbations

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

AA


23

Assign

CTAs to

Airlines

RBS

FCFS

Substitute

and Cancel


FAA FAAAirlines

Model 1: Airline Substitution and Cancellation Model

• Hedging

• Incorporates Speed Control into Decisions

Model 2: FAA Compression Model

• Adds speed control to current compression

framework

Model 1 Model 2

Airborne Flights:


ETAs, AC speeds

Flight on Ground:

Flight Schedule

Data

Algorithms

Allocations

Airline Decisions

GDP Timeline

Evolution of a GDP

24

Cstandard

CGDP

GDP

Capacity

Goal: We want to account for the possibility of

early clearance when assigning flights.

tstart tendtc1 tc2 tc3 tc4

GDP

Activity

GDP Timelinetstart tendtc1 tc2 tc3 tc4

Evolution of a GDP

25

tc1

tc2

tc3

tc4

tend

Yes Yes Yes Yes Yes

Scenario TreeGDP Timelinetstart tendtc1 tc2 tc3 tc4

GDP

Activity

Model 1: Airline Substitution and Cancellation

26

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Stage 1:

Initial

Assignment

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Slots

Allocated

with RBS


27

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Stage 1:

Initial

Assignment

DAL201:5:06

DAL142:5:10

DAL

Other Airlines


28

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Stage 1:

Initial

Assignment

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Cancelled Flights


29

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Stage 1:

Initial

Assignment

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Cancelled Flights


30

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Feasible

Range

without

Holding

Stage 1:

Initial

Assignment

Stage 2:

Revised

Assignment

Feasible

Range

with Holding

Cancelled Flights

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42


31

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Stage 1:

Initial

Assignment

Stage 2:

Revised

Assignment

Cancelled Flights

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Incorporates

Planning over

Multiple

Scenarios

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42


32

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Stage 1:

Initial

Assignment

Stage 2:

Revised

Assignment

Cancelled Flights

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Airlines can choose to

remain in original slot if

they expect no early

weather clearance in

scenario.

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42


33

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Stage 1:

Initial

Assignment

Stage 2:

Revised

Assignment

Cancelled Flights

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Airlines can also fly

faster if they expect the

weather to clear early in

the scenario.

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42


34

Flight

DAL53:5:03

Arrival Time

S1-5:10

S2-5:12

S3-5:14

S4-5:16

S5-5:18

S6-5:20

Arrival Time

S1-5:08

S2-5:10

S3-5:12

S4-5:14

S5-5:18

S22-5:42

Stage 1:

Initial

Assignment

Stage 2:

Revised

Assignment

Cancelled Flights

DAL201:5:06

DAL142:5:10

DAL

Other Airlines

Objective: Each airline

minimizes the total expected

cost of assignments and

cancellations over all

scenarios.

Model 2: Compression

35

Compression

Flight

UA53-5:00

UA183-5:05

Airport

S1-5:00

S2-5:04

S3-5:06

S4-5:09

S5-5:12

S6-5:15

AA561-4:58

DAL12-5:03

DAL490-5:06

AA321-5:11

Flight

UA53-5:00

UA183-5:05

Airport

S1-5:00

S2-5:04

S3-5:06

S4-5:09

S5-5:12

S6-5:15

AA561-4:58

DAL12-5:03

DAL490-5:06

AA321-5:11

RBS++ : Vossen and Ball [2006] with

speed control

Impact of Changes on Airline Costs

• The proposed changes have potential to reduce

airline costs

– Airlines can choose whether to prioritize cancellations

or delay

– End result is fewer missed connections and/or better

customer service

• Computational experiment was conducted to

evaluate potential cost savings

– GDP cancellation probabilities and amount of ground

delay recovered was taken from Inniss and Ball1

– Examined GDP cost savings under various early

weather clearance scenarios361Inniss, T.R., Ball, M.O., 2004. Estimating one-parameter airport arrival capacity distributions for air traffic flow management.

Air Traffic Control Quarterly 12, 223–251.

Airline Cost Model

• Adopted cost model used by Vakili and Ball (ATM seminar 2009)

• Approach assumes block time is free during first 15 min, then $32 per

min on the ground and $64 in the air

• We assume equal cost of ground and air delay of $40 after first 15 min

• Model also assumes airlines take delay cost of $0.1 per min

• Updating to 2013 airline costs reach $0.125 per min

• Parameters

– P: Number of passengers of aircraft

– x: Minutes of flight delay

– Mp: The delay threshold beyond which it becomes cost effective to cancel the flight

37

pp

p

MxMP

MxxP

x

PxC

15125.040

1515125.040

150

),(

Experimental Test Conditions

• Data Source: TFMS and ASDX files

• Airport: ATL

• Date of Flights: May 1, 2011

• 5-hour GDP

• Aircraft speeds ranged from Mach 0.72-0.85

• Capacity reduced to 40 flights per hour

• Load Factor of 0.8

• Flight cancellation costs equal delay costs at 120 min

• Exemption Radius of 1000 nm for Conventional GDPs

38

Cost Savings under Early Cancellation

39

• CTA assignment leads to significant cost savings

when the weather clears sufficiently early

• Earlier departure times allow for greater delay

recovery

0.00

50,000.00

100,000.00

150,000.00

200,000.00

250,000.00

300,000.00

350,000.00

0 1 2 3 4 >=5

Co

st (

$)

Clearance Time

Conventional Winter Spring Spring

Cost Savings under Early Cancellation

40

• CTA assignment leads to significant cost savings

when the weather clears sufficiently early

• Earlier departure times allow for greater delay

recovery

0 19.56 22.32 22.32

1 19.46 22.21 22.21

2 17.47 19.87 19.09

3 5.51 6.25 5.72

4 1.75 1.72 1.23

>=5 1.57 1.54 1.06

Cancellation

HourWinter Spring Summer

Percentage Cost Savings

Experimental Test Conditions

• Data Source: TFMS and ASDX files

• Airport: ATL

• Date of Flights: May 1, 2011

• 5-hour GDP

• Aircraft speeds ranged from Mach 0.72-0.85

• Capacity reduced to 40 flights per hour

• Load Factor of 0.8

• Flight cancellation costs equal delay costs at 90 min

• Exemption Radius of 1000 nm for Conventional GDPs

• Uniform Probabilities for scenarios

40

Cancellations and Substitutions

• Assumed up to 60 minutes of early GDP clearance

• Proposed changes lead to fewer cancellations and

more delay

42

Conventional

GDPCTA Based GDP

Conventional

GDPCTA Based GDP

Conventional

GDPCTA Based GDP

Delta (DAL) 27.78 24.07 11.14 25.4 108 108

Air Tran (TRS) 32.14 28.57 12.37 18.02 28 28

American

Southeast

(ASQ)

27.59 17.24 18.29 19.24 58 58

American

(AAL)33.33 33.33 46.5 25 3 3

Pinnacle

(FLG)25 0 29.25 37.75 4 4

Percentage of Flights Cancelled Passenger Delay Number of Flights

Airline

Cancellations and Substitutions

• Assumed up to 30 minutes of early GDP clearance

• Proposed changes lead to fewer cancellations and

more delay

Percentage of Cancellations Minutes of Delay per Flight

0

10

20

30

40

50

DAL TRS ASQ AAL FLG

Min

ute

s o

f D

elay

Conventional CTA Based

0

5

10

15

20

25

30

35

DAL TRS ASQ AAL FLG

Conventional CTA Based

42

Effect of Exemption Radius

• Used integer programming models seeded from DB-RBS

instead of RBS

• The addition of the exemption radius transfers delay from

DAL and TRS to regional Airlines ASQ

44

Percentage of Cancellations Minutes of Delay per Flight

0

10

20

30

40

50

60

DAL TRS ASQ AAL FLG

Min

ute

s o

f D

elay

With Radius Without Radius

0

5

10

15

20

25

30

35

DAL TRS ASQ AAL FLG

With Radius Without Radius

Impact of Early Cancellation

• Early cancellation is more helpful to

dominant carriers with more long haul

flights

45

Minutes of Delay Recovered

Impact of Early Cancellation

• Early cancellation is more helpful to

dominant carriers with more long haul

flights

46

Minutes of Delay Recovered per Flight

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

DAL TRS ASQ AAL FLG

Min

ute

s o

f D

ela

y p

er F

ligh

t

0 15 30 45 60

Summary and Future Work

• Proposed a new strategy for managing GDPs

– Control by CTA

– En Route Speed Control

– Eliminated Exemption Radius

• Strategy provides opportunities for significant cost savings

• Strategy may lead to airline behavioral changes

– Fewer cancellations

– More delay

• Near Term Challenges

– Compliance

– Modifying current procedures

• Long Term Challenges

– Need to reconcile flexibility with Trajectory Based Operations

– Managing flights with dynamic adjustment

47

Combining Control by CTA and Dynamic En Route Speed ...

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